• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Wrist-Type Fall Detector with Statistical Classifier for the Elderly Care


Abstract

Falls are one of the most concerned accidents for elderly people and often result in serious physical and psychological consequences. Many researchers have studied fall detection techniques in various domain, however none released to a commercial product satisfying user requirements. We present a systematic modeling and evaluating procedure for best classification performance and then do experiments for comparing the performance of six procedures to get a statistical classifier based wrist-type fall detector to prevent dangerous consequences from falls. Even though the wrist may be the most difficult measurement location on the body to discern a fall event, the proposed feature deduction process and fall classification procedures shows positive results by using data sets of fall and general activity as two classes.


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Cite this article

[IEEE Style]
Chankyu Park, Jaehong Kim, Joo-chan Sohn and Ho-Jin Choi, "A Wrist-Type Fall Detector with Statistical Classifier for the Elderly Care," KSII Transactions on Internet and Information Systems, vol. 5, no. 10, pp. 1751-1769, 2011. DOI: 10.3837/tiis.2011.10.004

[ACM Style]
Park, C., Kim, J., Sohn, J., and Choi, H. 2011. A Wrist-Type Fall Detector with Statistical Classifier for the Elderly Care. KSII Transactions on Internet and Information Systems, 5, 10, (2011), 1751-1769. DOI: 10.3837/tiis.2011.10.004